The most common mistake is hiring someone who can call a model API and assuming that's the same as someone who can build one.
Your Klysera ML engineer owns the full lifecycle from raw data to trained model to production deployment, so every training cycle moves your product forward instead of quietly draining your runway.
Build models so good, your product becomes the industry's benchmark.
Scale what you're building with AI-native ML engineers who are rigorously vetted, fully enabled, and managed end-to-end so every model you ship gets more accurate, and your product's intelligence becomes the reason users stay.
Trusted By Global Tech Teams Building The Future
THE FUTURE OF MACHINE LEARNING ENGINEERING
You don't need a $2M compute budget to turn your data into a real advantage.
There's a version of your product where every user interaction makes the next experience better. Most founders never get there, because building and training models properly requires a different discipline than wiring up an API call.
An ML engineer builds the training pipelines, the feature engineering, and the evaluation systems that turn your raw data into a model that compounds in value the longer your product exists, instead of staying exactly as smart as the day you integrated it.
YOUR MACHINE LEARNING ENGINEERING ADVANTAGE
The engineering
Talent partner your product has been waiting for.
Talent partner your product has been waiting for.
See the Impact Agreement
BUILT FOR THE WAY YOU BUILD
World-class ML engineers built around the work that turns your data into a real advantage.
Model Training & Experimentation
Problem
No Handoff
Scope
Designs training runs, architecture choices, and experimentation frameworks that systematically improve model performance at every stage of your product.
Evaluation & Validation
Problem
No Handoff
Scope
Builds rigorous evaluation frameworks that test for accuracy, bias, edge cases, and failure modes, so a model never ships on the strength of a single impressive demo.
Fine-Tuning & Domain Adaptation
Problem
No Handoff
Scope
Adapts foundation models to your domain, your data, and your users, so the model performs like it was built for your product, not borrowed from someone else's.
Deployment & Serving Infrastructure
Problem
No Handoff
Scope
Architects the serving infrastructure, latency optimisation, and scaling systems that keep your model fast and reliable under real production load.
SUCCESS IN NUMBERS
The best return on your engineering investment.
Companies that hire through Klysera get a measurable shift in how their infrastructure performs, what it costs, and how fast their team can ship on top of it.
60%
Cost savings compared to traditional hiring models
5-Point
IKE framework every engineer is stress-tested against to ensure they meet the set benchmarks
$0
Is our fee if your engineer doesn't hit the benchmarks we agreed before they started.
100%
Of all Klysera's engagements are outcome-based, so you only pay for results.
THE FUTURE OF MACHINE ENGINEERING
We Built The Framework To Get You The Rarest Type of Builders
Most founder conversations with talent partners feel like being sold to. Ours don't. Here's exactly what happens from the moment you book to the moment your engineer is working on your product:
OUR SERVICES
Great ML engineers don't just train models. They build intelligence that compounds.
From your first dataset to the model that becomes the reason your product can't be replicated by a competitor calling the same API, every Klysera ML engineer shows up ready to own the work that determines whether your product's intelligence is a genuine advantage or a rented one.
Data & Feature Engineering
Data pipeline design & ingestion architecture
Feature engineering & feature store design
Data labelling strategy & quality assurance
Training dataset curation & versioning
Model Development & Training
Model architecture selection & design
Training pipeline design & experimentation frameworks
Hyperparameter tuning & optimisation
Transfer learning & fine-tuning strategy
Evaluation & Validation
Evaluation framework design & benchmarking
Bias detection & fairness testing
Edge case & failure mode analysis
A/B testing for model versions
Deployment, Monitoring & Retraining
Model serving infrastructure & latency optimization
Production monitoring & drift detection
Automated retraining pipeline design
Model versioning & rollback systems
KLYSERA VS. THE ALTERNATIVES
Hiring or outsourcing? Neither.
Work with world-class AI-native mobile engineers who are fully vetted, enabled, and backed by a guarantee built around your outcomes.
Klysera
We define what success looks like together — specific, measurable outcomes your engineer is expected to deliver.
Traditional staffing
They hand you resumes and hope for the best. No accountability after placement.
In-house hiring
Full control, but slow, expensive, and you're gambling on interviews alone.
Outsourced dev shops
They build it for you, but you lose control, context, and the ability to iterate on your own terms.
AI-Native Talent
Klysera
Traditional staffing
In-house hiring
Outsourced dev shops
End-to-End Ownership
Klysera
Traditional staffing
In-house hiring
Outsourced dev shops
Performance Guarantee
Klysera
Traditional staffing
In-house hiring
Outsourced dev shops
Ongoing Enablement
Klysera
Traditional staffing
In-house hiring
Outsourced dev shops
Cost Efficiency
Klysera
Traditional staffing
In-house hiring
Outsourced dev shops
Impact Agreement
Klysera
Traditional staffing
In-house hiring
Outsourced dev shops
OUR WORK
Here's what happens when a ML engineer treats your infrastructure like it's their own.
"Our cloud bill had tripled in 18 months and nobody could tell me why. The Klysera engineer we brought in audited everything, cut $38K in monthly spend, and rebuilt our deployment pipeline in six weeks. We went from shipping fortnightly to shipping daily. That's not an infrastructure win — that's a product win."
Daniel R. · CTO
Series B SaaS · Remote
"We had 14 infrastructure vulnerabilities flagged two weeks before our biggest enterprise sales call. Klysera's cloud engineer closed every one and had our compliance documentation ready before the meeting. We closed the client. That engineer paid for themselves in one deal."
Sarah M. · CEO
AI Startup · London
"We had no infrastructure, no DevOps, nothing. Just a product that needed to exist. Klysera built the entire cloud foundation from scratch — architecture, CI/CD, security baseline — and stayed with us through the seed round. Investors were asking about our technical foundation. For the first time, we had a real answer."
Yoav B. · VP Engineering
Fintech · Tel Aviv
"We were burning through compute budget and our unit economics didn't make sense. The inference infrastructure Klysera built reduced our per-request cost by 64%. That number is what got us to Series A. I'm not exaggerating."
Noa T. · Founder
Pre-Seed · Remote
OUR DIFFERENCE
Klysera is built for founders who refuse to settle.
Accountable:
We monitor delivery against the benchmarks we agreed before work began, step in when things drift, and stay accountable for outcomes long after the onboarding call is over.
Precise:
We match you to the engineer whose specific experience maps to your specific inflection point in a company that looked like yours.
Enabling
Every Klysera engineer arrives with more than technical skills. They arrive equipped with the frameworks, tooling, and ongoing support to deliver from day one and stay consistent throughout the engagement.
Seamless
You always know where your engineer stands, what they're working on, and whether the benchmarks are being hit.
YOUR PRODUCT DESERVES BETTER
We only work with the best engineers to ensure maximum product quality
Fewer than one in five engineers who enter the Klysera assessment pass the IKE standard, because owning retention, making the right platform call, navigating App Store compliance, and integrating on-device AI simultaneously is a specific capability most hiring processes never screen for.
A NEW STANDARD FOR YOUR PRODUCT
You didn't build something worth scaling just to watch it hit a ceiling your architecture can't support
There's a better way to build. And it's not another job board search, another agency retainer that disappears when the performance ceiling appears, or another freelancer who makes the framework call based on what they know rather than what your product needs.
Experience a new standard in machine learning engineering.
Let's talk about what you're building and find the engineer who's made those decisions correctly before.
